Projects per year
Abstract
Cycling is a key ingredient for a sustainability shift of Denmark's transportation system. To increase cycling rates, better bicycle infrastructure networks are required. Planning such networks requires high-quality infrastructure data, yet the quality of bicycle infrastructure data is understudied. Here, we compare the two largest open data sets on dedicated bicycle infrastructure in Denmark, OpenStreetMap (OSM) and GeoDanmark, in a countrywide data quality assessment, asking whether the data are good enough for network-based analysis of cycling conditions. We find that neither of the data sets is of sufficient quality, and that data conflation is necessary to obtain a more complete data set. Our analysis of the spatial variation of data quality suggests that rural areas are more prone to incomplete data. We demonstrate that the prevalent method of using infrastructure density as a proxy for data completeness is not suitable for bicycle infrastructure data, and that matching of corresponding features is thus necessary to assess data completeness. Based on our data quality assessment, we recommend strategic mapping efforts toward data completeness, consistent standards to support comparability between different data sources, and increased focus on data topology to ensure high-quality bicycle network data.
Original language | Danish |
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Journal | Geographical Analysis |
Number of pages | 36 |
ISSN | 1538-4632 |
DOIs | |
Publication status | Published - 2024 |
Keywords
- bicycle networks
- Open data
- spatial data quality
- OpenStreetMap
- bicycle infrastructure
Datasets
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BikeDNA BIG: Denmark analysis
Vierø, A. R. (Creator), ZENODO, 13 Sept 2023
DOI: 10.5281/zenodo.8340383, https://zenodo.org/records/8340383
Dataset
Projects
- 1 Active
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NADanBI: Network analysis of the Danish bicycle infrastructure
Szell, M. (PI) & Vierø, A. R. (CoI)
01/01/2022 → 31/03/2025
Project: Research